Vincent Cuevas

This research explores how service area delineation techniques can be applied to estimate the population serviced by municipally operated indoor swimming pools in 2020 and 2025 in the City of Toronto, Ontario, Canada. Municipalities face financial costs and the need to serve a growing population as challenges to providing access to pool facilities across Toronto. Comparing deterministic and probabilistic service area delineation techniques and analyzing service area demographics are steps to identify if these pool facilities are accessible across the city. Deterministic service areas using radius buffers and drive-distance buffers were created with a 2km travel cost, while the Huff Model used census tracts with a probability of 0.20 to determine its service area. The results of this study showed that deterministic service area techniques create larger service area populations than the probabilistic Huff Model, and that the demographic composition of the populations have slightly higher proportions of lower-income households, and lower proportions of visible minorities. The addition of six new indoor pool facilities planned for completion by 2025 will service both highly populated areas and lower populated areas with differing demographics.